413 resultados para Monitor


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Introduction Since 1992 there have been several articles published on research on plastic scintillators for use in radiotherapy. Plastic scintillators are said to be tissue equivalent, temperature independent and dose rate independent [1]. Although their properties were found to be promising for measurements in megavoltage X-ray beams there were some technical difficulties with regards to its commercialisation. Standard Imaging has produced the first commercial system which is now available for use in a clinical setting. The Exradin W1 scintillator device uses a dual fibre system where one fibre is connected to the Plastic Scintillator and the other fibre only measures Cerenkov radiation [2]. This paper presents results obtained during commissioning of this dosimeter system. Methods All tests were performed on a Novalis Tx linear accelerator equipped with a 6 MV SRS photon beam and conventional 6 and 18 MV X-ray beams. The following measurements were performed in a Virtual Water phantom at a depth of dose maximum. Linearity: The dose delivered was varied between 0.2 and 3.0 Gy for the same field conditions. Dose rate dependence: For this test the repetition rate of the linac was varied between 100 and 1,000 MU/min. A nominal dose of 1.0 Gy was delivered for each rate. Reproducibility: A total of five irradiations for the same setup. Results The W1 detector gave a highly linear relationship between dose and the number of Monitor Units delivered for a 10 9 10 cm2 field size at a SSD of 100 cm. The linearity was within 1 % for the high dose end and about 2 % for the very low dose end. For the dose rate dependence, the dose measured as a function of repetition the rate (100–1,000 MU/min) gave a maximum deviation of 0.9 %. The reproducibility was found to be better than 0.5 %. Discussion and conclusions The results for this system look promising so far being a new dosimetry system available for clinical use. However, further investigation is needed to produce a full characterisation prior to use in megavoltage X-ray beams.

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Purpose The purpose of this study was to evaluate age and gender differences in objectively measured physical activity (PA) in a population-based sample of students in grades 1–12. Methods Participants (185 male, 190 female) wore a CSA 7164 accelerometer for 7 consecutive days. To examine age-related trends, students were grouped as follows: grades 1–3 (N = 90), grades 4–6 (N = 91), grades 7–9 (N = 96), and grades 10–12 (N = 92). Bouts of PA and minutes spent in moderate-to-vigorous PA (MVPA) and vigorous PA (VPA) were examined. Results Daily MVPA and VPA exhibited a significant inverse relationship with grade level, with the largest differences occurring between grades 1–3 and 4–6. Boys were more active than girls; however, for overall PA, the magnitudes of the gender differences were modest. Participation in continuous 20-min bouts of PA was low to nonexistent. Conclusion Our results support the notion that PA declines rapidly during childhood and adolescence and that accelerometers are feasible alternatives to self-report methods in moderately sized population-level surveillance studies.

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Purpose The purpose of this review is to address important methodological issues related to conducting accelerometer-based assessments of physical activity in free-living individuals. Methods We review the extant scientific literature for empirical information related to the following issues: product selection, number of accelerometers needed, placement of accelerometers, epoch length, and days of monitoring required to estimate habitual physical activity. We also discuss the various options related to distributing and collecting monitors and strategies to enhance compliance with the monitoring protocol. Results No definitive evidence exists currently to indicate that one make and model of accelerometer is more valid and reliable than another. Selection of accelerometer therefore remains primarily an issue of practicality, technical support, and comparability with other studies. Studies employing multiple accelerometers to estimate energy expenditure report only marginal improvements in explanatory power. Accelerometers are best placed on hip or the lower back. Although the issue of epoch length has not been studied in adults, the use of count cut points based on 1-min time intervals maybe inappropriate in children and may result in underestimation of physical activity. Among adults, 3–5 d of monitoring is required to reliably estimate habitual physical activity. Among children and adolescents, the number of monitoring days required ranges from 4 to 9 d, making it difficult to draw a definitive conclusion for this population. Face-to-face distribution and collection of accelerometers is probably the best option in field-based research, but delivery and return by express carrier or registered mail is a viable option. Conclusion Accelerometer-based activity assessments requires careful planning and the use of appropriate strategies to increase compliance.

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This study was undertaken to investigate any relationship between sensory features and neck pain in female office workers using quantitative sensory measures to better understand neck pain in this group. Office workers who used a visual display monitor for more than four hours per day with varying levels of neck pain and disability were eligible for inclusion. There were 85 participants categorized according to their scores on the neck disability index (NDI): 33 with no pain (NDI < 8); 38 with mild levels of pain and disability (NDI 9–29); 14 with moderate levels of pain (NDI ⩾ 30). A fourth group of women without neck pain (n = 22) who did not work formed the control group. Measures included: thermal pain thresholds over the posterior cervical spine; pressure pain thresholds over the posterior neck, trapezius, levator scapulae and tibialis anterior muscles, and the median nerve trunk; sensitivity to vibrotactile stimulus over areas of the hand innervated by the median, ulnar and radial nerves; sympathetic vasoconstrictor response. All tests were conducted bilaterally. ANCOVA models were used to determine group differences between the means for each sensory measure. Office workers with greater self-reported neck pain demonstrated hyperalgesia to thermal stimuli over the neck, hyperalgesia to pressure stimulation over several sites tested; hypoaesthesia to vibration stimulation but no changes in the sympathetic vasoconstrictor response. There is evidence of multiple peripheral nerve dysfunction with widespread sensitivity most likely due to altered central nociceptive processing initiated and sustained by nociceptive input from the periphery.

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This study explored the interaction between physical and psychosocial factors in the workplace on neck pain and disability in female computer users. A self-report survey was used to collect data on physical risk factors (monitor location, duration of time spent using the keyboard and mouse) and psychosocial domains (as assessed by the Job Content Questionnaire). The neck disability index was the outcome measure. Interactions among the physical and psychosocial factors were examined in analysis of covariance. High supervisor support, decision authority and skill discretion protect against the negative impact of (1) time spent on computer-based tasks, (2) non-optimal placement of the computer monitor, and; (3) long duration of mouse use. Office workers with greater neck pain experience a combination of high physical and low psychosocial stressors at work. Prevention and intervention strategies that target both sets of risk factors are likely to be more successful than single intervention programmes. Statement of Relevance The results of this study demonstrate that the interaction of physical and psychosocial factors in the workplace has a stronger association with neck pain and disability than the presence of either factor alone. This finding has important implications for strategies aimed at the prevention of musculoskeletal problems in office workers.

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Objective To investigate how and when changes in workplace sitting time occurred following a workplace intervention to inform evaluation of intervention success. Method The 4-week Stand Up Comcare study (June–September 2011) aimed to reduce workplace sitting time via regularly interrupting and replacing sitting time throughout the day. Activity monitor (activPAL3) workplace data from control (n=22) and intervention participants (n=21) were analysed. Differences in the number and usual duration of sitting bouts were used to evaluate how change occurred. To examine when change occurred, intervention effects were compared by hour since starting work and hour of the workday. Change in workplace activity (sitting, standing, stepping) was examined to further inform alignment with intervention messages. Individual variability was examined in how and when the change occurred. Results Overall, behavioural changes aligned with intervention aims. All intervention participants reduced total workplace sitting time, though there was wide individual variability observed (range −29 to −262 min per 8 h workday). On average, intervention participants reduced number of sitting bouts (−4.6 bouts (95% CI −10.1 to 1.0), p=0.106) and usual sitting bout duration (−5.6 min (95% CI −9.8 to −1.4, p=0.011)) relative to controls. Sitting time reductions were observed across the workday, though intervention effects varied by hour of the day (p=0.015). The intervention group successfully adopted the Stand Up and Sit Less intervention messages across the day. Conclusion These analyses confirmed that this workplace intervention successfully modified sitting behaviour as intended (ie, fewer and shorter sitting bouts, with changes occurring throughout the day).

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In this study, we evaluated agreement among three generations of ActiGraph (TM) accelerometers in children and adolescents. Twenty-nine participants (mean age = 14.2 +/- 3.0 years) completed two laboratory-based activity sessions, each lasting 60 min. During each session, participants concurrently wore three different models of the ActiGraph (TM) accelerometers (GT1M, GT3X, GT3X+). Agreement among the three models for vertical axis counts, vector magnitude counts, and time spent in moderate-to-vigorous physical exercise (MVPA) was evaluated by calculating intraclass correlation coefficients and Bland-Altman plots. The intraclass correlation coefficient for total vertical axis counts, total vector magnitude counts, and estimated MVPA was 0.994 (95% CI = 0.989-0.996), 0.981 (95% CI = 0.969-0.989), and 0.996 (95% CI = 0.989-0.998), respectively. Inter-monitor differences for total vertical axis and vector magnitude counts ranged from 0.3% to 1.5%, while inter-monitor differences for estimated MVPA were equal to or close to zero. On the basis of these findings, we conclude that there is strong agreement between the GT1M, GT3X, and GT3X+ activity monitors, thus making it acceptable for researchers and practitioners to use different ActiGraph (TM) models within a given study.

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Background Wearable monitors are increasingly being used to objectively monitor physical activity in research studies within the field of exercise science. Calibration and validation of these devices are vital to obtaining accurate data. This article is aimed primarily at the physical activity measurement specialist, although the end user who is conducting studies with these devices also may benefit from knowing about this topic. Best Practices Initially, wearable physical activity monitors should undergo unit calibration to ensure interinstrument reliability. The next step is to simultaneously collect both raw signal data (e.g., acceleration) from the wearable monitors and rates of energy expenditure, so that algorithms can be developed to convert the direct signals into energy expenditure. This process should use multiple wearable monitors and a large and diverse subject group and should include a wide range of physical activities commonly performed in daily life (from sedentary to vigorous). Future Directions New methods of calibration now use "pattern recognition" approaches to train the algorithms on various activities, and they provide estimates of energy expenditure that are much better than those previously available with the single-regression approach. Once a method of predicting energy expenditure has been established, the next step is to examine its predictive accuracy by cross-validating it in other populations. In this article, we attempt to summarize the best practices for calibration and validation of wearable physical activity monitors. Finally, we conclude with some ideas for future research ideas that will move the field of physical activity measurement forward.

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The purpose of this study was to determine whether physical activity behavior tracks during early childhood. Forty-seven children (22 males, 25 females) aged 3-4 yr at the beginning of the study were followed over a 3-yr period. Heart rates were measured at least 2 and up to 4 d . yr(-1) with a Quantum XL Telemetry heart rate monitor. Physical activity was quantified as the percentage of observed minutes between 3:00 and 6:00 p.m. during which heart rate was 50% or more above individual resting heart rate (PAHR-50 Index). Tracking of physical activity was analyzed using Pearson and Spearman correlations. Yearly PAHR-50 index tertiles were created and examined for percent agreement and Cohen's kappa. Repeated measures ANOVA was used to calculate the intraclass correlation coefficient across the 3 yr of the study. Spearman rank order correlations ranged from 0.57 to 0.66 (P < 0.0001). Percent agreement ranged from 49% to 62%. The intraclass R for the 3 yr was 0.81. It was concluded that physical activity behavior tends to track during early childhood.

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Purpose This Study evaluated the predictive validity of three previously published ActiGraph energy expenditure (EE) prediction equations developed for children and adolescents. Methods A total of 45 healthy children and adolescents (mean age: 13.7 +/- 2.6 yr) completed four 5-min activity trials (normal walking. brisk walking, easy running, and fast running) in ail indoor exercise facility. During each trial, participants were all ActiGraph accelerometer oil the right hip. EE was monitored breath by breath using the Cosmed K4b(2) portable indirect calorimetry system. Differences and associations between measured and predicted EE were assessed using dependent t-tests and Pearson correlations, respectively. Classification accuracy was assessed using percent agreement, sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve. Results None of the equations accurately predicted mean energy expenditure during each of the four activity trials. Each equation, however, accurately predicted mean EE in at least one activity trial. The Puyau equation accurately predicted EE during slow walking. The Trost equation accurately predicted EE during slow running. The Freedson equation accurately predicted EE during fast running. None of the three equations accurately predicted EE during brisk walking. The equations exhibited fair to excellent classification accuracy with respect to activity intensity. with the Trost equation exhibiting the highest classification accuracy and the Puyau equation exhibiting the lowest. Conclusions These data suggest that the three accelerometer prediction equations do not accurately predict EE on a minute-by-minute basis in children and adolescents during overground walking and running. The equations maybe, however, for estimating participation in moderate and vigorous activity.

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Purpose To evaluate the validity of a uniaxial accelerometer (MTI Actigraph) for measuring physical activity in people with acquired brain injury (ABI) using portable indirect calorimetry (Cosmed K4b(2)) as a criterion measure. Methods Fourteen people with ABI and related gait pattern impairment (age 32 +/- 8 yr) wore an MTI Actigraph that measured activity (counts(.)min-(1)) and a Cosmed K4b(2) that measured oxygen consumption (mL(.)kg(-1.)min(-1)) during four activities: quiet sitting (QS) and comfortable paced (CP), brisk paced (BP), and fast paced (FP) walking. MET levels were predicted from Actigraph counts using a published equation and compared with Cosmed measures. Predicted METs for each of the 56 activity bouts (14 participants X 4 bouts) were classified (light, moderate, vigorous, or very vigorous intensity) and compared with Cosmed-based classifications. Results Repeated-measures ANOVA indicated that walking condition intensities were significantly different (P < 0.05) and the Actigraph detected the differences. Overall correlation between measured and predicted METs was positive, moderate, and significant (r = 0.74). Mean predicted METs were not significantly different from measured for CP and BP, but for FP walking, predicted METs were significantly less than measured (P < 0.05). The Actigraph correctly classified intensity for 76.8% of all activity bouts and 91.5% of light- and moderate-intensity bouts. Conclusions Actigraph counts provide a valid index of activity across the intensities investigated in this study. For light to moderate activity, Actigraph-based estimates of METs are acceptable for group-level analysis and are a valid means of classifying activity intensity. The Actigraph significantly underestimated higher intensity activity, although, in practice, this limitation will have minimal impact on activity measurement of most community-dwelling people with ABI.

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This paper presents a practical recursive fault detection and diagnosis (FDD) scheme for online identification of actuator faults for unmanned aerial systems (UASs) based on the unscented Kalman filtering (UKF) method. The proposed FDD algorithm aims to monitor health status of actuators and provide indication of actuator faults with reliability, offering necessary information for the design of fault-tolerant flight control systems to compensate for side-effects and improve fail-safe capability when actuator faults occur. The fault detection is conducted by designing separate UKFs to detect aileron and elevator faults using a nonlinear six degree-of-freedom (DOF) UAS model. The fault diagnosis is achieved by isolating true faults by using the Bayesian Classifier (BC) method together with a decision criterion to avoid false alarms. High-fidelity simulations with and without measurement noise are conducted with practical constraints considered for typical actuator fault scenarios, and the proposed FDD exhibits consistent effectiveness in identifying occurrence of actuator faults, verifying its suitability for integration into the design of fault-tolerant flight control systems for emergency landing of UASs.

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Belongingness has been linked to depression. Prior studies have been cross-sectional with few addressing distinct belongingness contexts. This study used structural equation modelling to investigate cross-lagged longitudinal relationships between general belonging, workplace belonging and depressive symptoms in a community sample of 221 working adults measured at two time points three months apart. Measures were: Sense of Belonging Instrument-Psychological (SOBI-P); Psychological Sense of Organizational Membership (PSOM); Depression Anxiety Stress Scales (DASS-21); Kessler Psychological Distress Scale (K10). General belonging was predicted more strongly by depressive symptoms than by baseline general belonging, suggesting that depressive symptoms not only linger but also influence future belongingness cognitions. Neither general nor workplace belonging longitudinally predicted depressive symptoms, however cross-sectional correlations were substantial. The concurrent path between general belongingness and depressive symptoms was strong. Results are consistent with daily process studies suggesting that reduced belongingness precipitates a rapid increase in depressive symptoms which influence longer term belongingness cognitions. Congruent with interpersonal descriptions of depression such as the social-cognitive interpersonal process model, results further suggest that belongingness cognitions are the proximal antecedent of a depressive response. Practitioners should monitor both a general sense of belonging as well as perceived relational value cues in specific contexts.

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In order to effectively measure the physical activity of children, objective monitoring devices must be able to quantify the intermittent and nonlinear movement of free play. The purpose of this study was to investigate the validity of the Computer Science and Applications (CSA) uniaxial accelerometer and the TriTrac-R3D triaxial accelerometer with respect to their ability to measure 8 "free-play" activities of different intensity. The activities ranged from light to very vigorous in intensity and included activities such as throwing and catching, hopscotch, and basketball. Twenty-eight children, ages 9 to 11, wore a CSA and a heart rate monitor while performing the activities. Sixteen children also wore a Tritrac. Counts from the CSA, Tritrac, and heart rates corresponding to the last 3 min of the 5 min spent at each activity were averaged and used in correlation analyses. Across all 8 activities, Tritrac counts were significantly correlated with predicted MET level (r= 0.69) and heart rate (r= 0.73). Correlations between CSA output, predicted MET level (0.43), and heart rate (0.64) were also significant but were lower than those observed for the Tritrac. These data indicate that accelerometers are an appropriate methodology for measuring children's free-play physical activities.

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The purpose of this study was to examine the validity of the 3-Day Physical Activity Recall (3DPAR) self-report instrument in a sample of eighth and ninth grade girls (n = 70, 54.3% white, 37.1% African American). Criterion measures of physical activity were derived using the CSA 7164 accelerometer. Participants wore a CSA monitor for 7 consecutive days and completed the self-report physical activity recall for the last 3 of those days. Self-reported total METs, 30-min blocks of MVPA, and 30-min blocks of VPA were all significantly correlated with analogous CSA variables for 7 days (r = 0.35-0.51; P < 0.01) and 3 days (r = 0.27-0.46; P < 0.05) of monitoring. The results indicate that the 3DPAR is a valid instrument for assessing overall, vigorous, and moderate to vigorous physical activity in adolescent girls.